Integrative multi-omics and machine learning reveals the spatial niche distribution and role of CYP27A1(+)TAMs in immunotherapy response in non-small cell lung cancer

整合多组学和机器学习揭示了CYP27A1(+)TAMs在非小细胞肺癌免疫治疗反应中的空间分布和作用

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Abstract

BACKGROUND: The response rate to immune checkpoint blockade (ICB) in non-small cell lung cancer (NSCLC) varies significantly among individuals. Cancer-associated macrophages (TAMs) are key components of the tumor immune microenvironment (TIME), influencing tumor proliferation, metastasis, immune cell recruitment, and activation through diverse mechanisms. Their high heterogeneity, particularly in the context of immunotherapy, warrants further investigation. METHODS: We integrated single-cell and spatial transcriptomic data from the same patients using ISCHIA to construct nine spatial niches(local cellular communities). The composition of these niches was compared across different spatial regions and between samples with varying ICB treatment responses. CYP27A1(+)TAMs, identified as critical in ICB-responsive groups, were validated through external cohorts, immunohistochemistry, immunofluorescence, and in vivo experiments. RESULTS: Spatial niche analysis revealed that niche 9, which was enriched with effector cells, was found exclusively in ICB responders. CYP27A1(+)TAMs were a key component of this niche, recruiting CD8(+)T cells via antigen presentation and chemokine secretion, thereby improving patient prognosis. Based on this, we developed an accurate prognostic model. Following ICB treatment, these macrophages exhibited further activation of LXR and enhanced anti-apoptotic capabilities. In vivo and morphological experiments demonstrated that CYP27A1(+)TAMs effectively suppressed tumor growth and increased CD8(+)T cells infiltration in the TIME. CONCLUSION: This study highlights the importance of spatial niches in understanding the TIME of NSCLC and predicting ICB responses. CYP27A1(+)TAMs and their downstream LXR pathway provide a novel research direction for exploring potential biomarkers for personalized NSCLC management.

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